A commercial gamma ray detector includes an array of scintillator crystals coupled to a transparent light guide, which distributes scintillation light over an array of photomultiplier tubes (PMTs) arranged over the transparent light guide. A position of a gamma ray interaction within the array of scintillator crystals is generally encoded by spreading the optical signal corresponding to the gamma ray over several PMTs grouped into a neighborhood. By measuring relative signal intensities from each of the PMTs in the neighborhood and applying statistical methods or performing a centroid calculation, the location of the gamma ray is decoded. Signals from the PMTs corresponding to a neighborhood are generally summed in the analog domain, and then timing is measured based on the leading edge of the summed signal.
PMTs fast enough to support Time-of-Flight information are based on the ability to perform an ultra-fast analysis of a response to the scintillation light. Typically, as shown in FIGS. 1A-1C, the leading edge of the response is used for timing information, while the integral of the whole signal is used to establish the energy of the event.
Generally, the use of PMTs in a real system is made difficult because of two main factors: (1) extraction of the energy and timing of the event, and (2) handling of the highly variable rate of arrival of events.
Extraction of the energy and timing is non-trivial since it is usually performed in a noisy background. Triggering and filtering of this type of signal requires specialized analog electronics and a costly development effort. This task is further complicated by the fact that PMTs have intrinsic characteristics (gain, average transit time, etc.), which requires that the processing circuitry be adaptable to multiple conditions.
Regarding the variability of the count rate, most radiation detection processes follow a stochastic process that is very accurately described by Poisson's law, which stipulates that, on average, the time between events is the reciprocal of the number of counts collected in one second. However, in actuality, the time varies according to an exponential distribution. In practice, if one designs a system to accept one count every millisecond and the process is expected to generate one thousand counts per second, the system will only capture around 74% of the counts.
Accordingly, conventional detectors include highly adaptable front-end systems to adjust a multitude of parameters. In some instances, e.g., for gain adjustment, the dynamic range can become too large for the range of adjustment, and the sorting of parts is sometimes necessary. For example, PMTs with similar gains can be connected to one common sub-system to decrease the range this particular system has to handle. Further, to address problems with the count rate, a higher bandwidth system needs to be constructed so that fewer events are lost.
FIGS. 2A and 2B illustrate a conventional PET system, with the corresponding processing steps superimposed. Twelve PMTs are illustrated in FIG. 2A. First, each of the PMT output signals are pre-amplified using variable gain amplifiers, each of which has an adjustable gain and delay. See (1) and (2) in FIG. 2A. The pre-amplified signals are then split (3) into two sets, one for determining the timing of an event, and one for determining the energy of the event. The first set of signals are further split (4) prior to being input into a series of analog summers (7), corresponding to different trigger zones, in this case, five trigger zones. The summed signals are then passed to triggering circuits (8), which output the triggering signals to a digital processing circuit. Meanwhile, the second set of signals are shaped and filtered (5) and then converted to digital signals using quad analog-to-digital converters (6), and then passed to the digital processing circuit. The digital processing circuit uses algorithms to determine the position, timing, and energy of the event.